From cosmological simulations to binary black hole mergers: The impact of using analytical star formation history models on gravitational-wave source populations

TL;DR

This study evaluates how analytical models of cosmic star formation history impact the predicted properties of binary black hole mergers, revealing significant discrepancies with simulation-based models that affect gravitational-wave source population predictions.

Contribution

It demonstrates that common analytical star formation rate models can misrepresent merger rates and mass distributions, emphasizing the need for simulation-based approaches in gravitational-wave astrophysics.

Findings

Analytical models overestimate high-redshift merger rates by up to four orders of magnitude.

Spurious features in mass distributions are introduced by analytical models, such as an artificial 8 M_sun peak.

Simulation-based star formation histories provide more accurate predictions for BBH populations.

Abstract

Observations of binary black hole (BBH) mergers provide a unique window into the lives of massive stars across cosmic time. Connecting redshift-dependent merger properties to massive star progenitors requires accurate models of cosmic star formation and chemical enrichment histories. Analytical fits for the metallicity-specific cosmic star formation rate density S(Z, z) are commonly used as proxies for the complex underlying star formation history, yet they remain unconstrained. Using the IllustrisTNG cosmological simulations, we evaluate the accuracy of these analytical S(Z, z) prescriptions and assess how simulation resolution and volume affect the inferred S(Z, z). By coupling the simulated and analytical S(Z, z) to the population synthesis code COMPAS, we investigate the resulting BBH merger rates and mass distributions. We find that analytical S(Z, z) prescriptions can overestimate BBH merger rates at high redshift ($z \gtrsim 6$) by up to a factor of $10$-$10^4$, depending on cosmological simulation resolution, and can introduce spurious features in the BBH mass distribution. For example, they can produce an artificial feature near $8\,M_\odot$ in the primary mass distribution at $z \lesssim 2$, which is absent when using the full simulation-based S(Z, z), while simultaneously suppressing high-mass features. These discrepancies arise because simple analytical models fail to capture a high-metallicity bump and a more flattened low-metallicity tail in the simulated S(Z, z) metallicity distribution. Our results highlight the importance of accurate star formation histories for modeling BBH populations, demonstrate the limitation of widely used analytical S(Z, z) fits, and underscore the need for careful integration of cosmological simulations, analytical fits, and population synthesis when interpreting gravitational-wave observations.